code: def _csrsum(As, A_weights):
      """Return a graph whose adjacency matrix is the sparse matrix summation
      of the given list of graphs.
  
      Note that the edge weights of all graphs must be scalar, i.e. the arrays in
      :attr:`A_weights` must be 1D vectors.
  
      Parameters
      ----------
      As : list[HeteroGraphIndex]
          The input graph indices.
      A_weights : list[Tensor]
          The edge weights of graph A as 1D tensor.
  
      Returns
      -------
      C : HeteroGraphIndex
          The output graph index.
      C_weights : Tensor
          The edge weights of the output graph.
      """
      C, C_weights = _CAPI_DGLCSRSum(
          As, [F.to_dgl_nd(w) for w in A_weights]
      )
      return C, F.from_dgl_nd(C_weights)
  
imports: from __future__ import absolute_import
  from .None import backend, ndarray
  from ._ffi.function import _init_api
  from .base import DGLError
label_desc: Use image node_id 20 for calling a global function with example usage: _csrsum(As, A_weights) and returns: C,  F